SPACEBORNE QUANTITATIVE ASSESSMENT OF PRIMARY PRODUCTION VARIATIONS IN THE ARCTIC OCEAN OVER THE PREVIOUS DECADE

• Published in: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
• Main Authors: Pozdnyakov, D., Petrenko, D.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2015
• Subjects: article; Verlagsveröffentlichung; Arctic; Arctic Ocean; Phytoplankton
• Online Access: https://doi.org/10.5194/isprsarchives-XL-7-W3-1041-2015; https://noa.gwlb.de/receive/cop_mods_00016735; https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00016690/isprsarchives-XL-7-W3-1041-2015.pdf; https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-7-W3/1041/2015/isprsarchives-XL-7-W3-1041-2015.pdf

Spaceborne one month averaged data, predominantly from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and partly from the Moderate Resolution Imaging Spectroradiometer (MODIS), were used to investigate changes in primary production (PP) by phytoplankton in the Arctic Ocean from 1998 till 2010. Several PP retrieval algorithms were tested against the collected in situ data, and it was shown that the algorithm by Behrenfeld and Falkowski gave the best results (with the coefficient of correlation, r equal to 0.8 and 0.75, respectively, for the pelagic and shelf zones. Based on the performed test, the Behrenfeld and Falkowski algorithm was further applied for determining both the annual PP in the Arctic and the PP trend over the aforementioned time period. The results of our analysis indicate that PP in the Arctic has increased by ~ 15.9% over 13 years. This finding, as well as the absolute annual values of PP remotely quantified in the present study, is at odds with analogous numerical assessments by other workers. These disagreements are thought to be due to differences in the applied methodologies of satellite data processing, such as cloud masking and determination of phytoplankton concentration within (i) overcast areas, and (ii) areas of massive growth of coccolithophore algae, as well as (iii) in the shelf zone prone to a significant influence of land and river runoff. Hindcast (a decadal long) and forecast projections of PP variations are performed.